A warm welcome, course overview, and an introduction to the world of databases — delivered live in class with no accompanying slide module.
Why databases exist, what RDBMS really means, the shape of a table, and a first look at the SQL language — DDL, DML, and the commands that run them.
Choosing the right types for your columns, strings, numbers, dates, and thinking about keys, nullability, and the first principles of good table design.
CREATE TABLE in practice, primary keys, foreign keys, compound keys, NOT NULL, UNIQUE, and the constraints that keep your data honest.
INSERT, UPDATE, DELETE for putting data in and changing it. ALTER TABLE for reshaping, DROP vs TRUNCATE for cleanup, and the basic SELECT statement with column projection.
Hands-on practice covering everything from the first block: schema design, data types, CREATE TABLE with constraints, plus INSERT, UPDATE, DELETE, and basic SELECT.
Narrowing down results — comparison and logical operators, BETWEEN, IN, IS NULL, and combining conditions to ask precise questions of your data.
Ordering results with ORDER BY, finding patterns with LIKE and wildcards, and keeping result sets tidy with LIMIT.
Put SELECT to work — write queries that filter, sort, and slice realistic datasets. From straightforward lookups to layered conditions.
Summarising data with COUNT, SUM, AVG, MIN, MAX — and slicing those summaries across categories using GROUP BY and HAVING.
Queries inside queries — scalar, row, and table subqueries; correlated vs uncorrelated; and the art of breaking a hard problem into smaller ones.
Bringing tables together — INNER, LEFT, RIGHT, and FULL joins; self-joins; and the mental model for combining data across a relational schema.
Realistic analysis tasks that combine aggregation, grouping, subqueries, and joins. Think like a data analyst answering stakeholder questions.
The finishing kit — VIEWs for reusable queries, TRANSACTIONS for safety, INDEXes for speed, and a tour of SQL patterns for real data analysis.
A capstone session that pulls the whole course together, schema design, queries, analysis, and advanced features, in one integrated exercise set.
Self-serve references you can browse outside class. Not covered in lectures, but worth knowing.